“What may set IBM apart is the sheer number of IoT playing fields it engages in addition to AI and analytics, including cloud, development tool set, services, device management, storage and security. Add to that its longstanding reach into enterprise and industrial IT."Where public clouds [such as Microsoft IoT Hub and AWS] have APIs, Watson has whole solutions," said Bret Greenstein, IBM's global vice president of Watson IoT offerings, which is not to say that IBM insists on provisioning end-to-end IoT deployments; certainly, as part of the IBM Cloud, the Watson IoT platform is all about cross-vendor integration.” Everyone plays with everyone else.

“The pattern in IoT is the same as the pattern in cloud; we're containerizing everything.”

From ransomware to botnets, malware takes seemingly endless forms, and it’s forever proliferating. Try as we might, the humans who would defend our computers from it are drowning in the onslaught, so they are turning to AI for help.

Cybersecurity firm Endgame released a large, open-source data set called EMBER (for “Endgame Malware Benchmark for Research”). EMBER is a collection of more than a million representations of benign and malicious Windows-portable executable files, a format where malware often hides. A team at the company also released AI software that can be trained on the data set. The idea is that if AI is to become a potent weapon in the fight against malware, it needs to know what to look for.

The goal was for the AI to engage in a series of reasoned arguments according to some pretty standard rules of debate: no awareness of the debate topic ahead of time, no pre-canned responses. Each side gave a four-minute introductory speech, a four-minute rebuttal to the other’s arguments, and a two-minute closing statement.

So the question is: did Project Debater simply not understand the criteria, or did it understand and choose not to engage on those terms? Watching the debate, I figured the answer was that it didn’t quite get it, but I wasn’t positive. I couldn’t tell the difference between an AI not being as smart as it could be and an AI being way smarter than I’ve seen an AI be before. It was a pretty cognitively dissonant moment. Like I said, unsettling.

Artificial intelligence is moving from science fiction to practical reality fast, and it's in banks' best interest to gear up now for the changes ahead. Here are some strategies to consider.

Already some AI pioneers have emerged in the financial industry just over the past year: Bank of New York Mellon's use of robotic process automation in trade settlement and other back-office operations; Nasdaq's search for signs of market tampering with an assist from AI; UBS' initiative to answer basic customer-service questions through Amazon's virtual assistant, Alexa; and USAA's development of its own virtual assistant.

Australia's ANZ Group has been using IBM's Watson in its wealth management division for three years. Watson can read and understand unstructured data found in contracts and other documents, comb through millions of data points in seconds, and learn how to draw conclusions from the data. It can assess a new customer's financial situation more quickly and comprehensively than a human being, and it never forgets anything. (https://www.americanbanker.com/news/anz-turns-to-ibms-watson-to-customize-wealthy-client-services)

PolicyPal allows customers to buy and manage their insurance policies via mobile. Watson was trained on PolicyPal's database of more than 9,000 insurance policies to be able to gauge the intent of customer queries intuitively, and answer their questions quickly.

It has also been trained to explain complex insurance jargon to consumers to improve their understanding of the various insurance products available to them. Watson Conversation uses natural language processing (NPL) and machine learning (ML) to simulate natural human conversation to put consumers at ease.

Leveraging blockchain for your IoT data offers new ways to automate business processes among your partners without setting up a complex and expensive centralized IT infrastructure. Blockchain’s data protection fosters stronger working relationship with your partners and greater efficiency as partners take advantage of the information provided.IBM Watson IoT Platform enables IoT devices to send data to private blockchain ledgers for inclusion in shared transactions with distributed records, maintained by consensus, and cryptographically hashed.

if the waves of change hit us unprepared – which we are now – they will wash away the medical system we know and leave it purely a technology-based service with no personal interaction. Such a complicated system should not be allowed to just wash away; it should be consciously and purposely redesigned, piece by piece

“If we wanted to figure out if a customer is pregnant, even if she didn’t want us to know, can you do that? ” Your shopping habits reveal even the most personal information — like when you’re going to have a baby.

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